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Found 7 papers, 1 papers with code
On Transferability of Driver Observation Models from Simulated to Real Environments in Autonomous Cars
For driver observation frameworks, clean datasets collected in controlled simulated environments often serve as the initial training ground.
Uncertainty-Aware Vehicle Energy Efficiency Prediction using an Ensemble of Neural Networks
We propose in this paper an ensemble learning approach based on deep neural networks (ENN) that is designed to reduce the predictive uncertainty and to output measures of such uncertainty.
Uncertainty-Aware Prediction of Battery Energy Consumption for Hybrid Electric Vehicles
We propose a data-driven approach which relies on real-world datasets including battery related attributes.
Semi-Autonomous Electric Vehicles in Platooning Mode and Their Effects on Travel Time: A Framework for Simulation Evaluation
Connected and Automated Vehicles (CAVs) have received a lot of attention in recent years.
Simulation-Based Impact of Connected Vehicles in Platooning Mode on Travel Time, Emissions and Fuel Consumption
Several approaches have been presented during the last decades to reduce carbon pollution from transportation.
Boosting Algorithms for Delivery Time Prediction in Transportation Logistics
A variety of solutions exist for short-term travel time predictions such as solutions that utilize real-time GPS data and optimization methods to track the path of a vehicle.
Autonomous Driving: Framework for Pedestrian Intention Estimationin a Real World Scenario
Rapid advancements in driver-assistance technology will lead to the integration of fully autonomous vehicles on our roads that will interact with other road users.
Autonomous Driving
Robotics
